If you are evaluating decentralized GPU clouds for AI workloads, you have probably come across both io.net and Aethir. They are the two most prominent DePIN (Decentralized Physical Infrastructure Network) compute projects, each with large networks, active tokens, and ambitious roadmaps. But they serve different use cases, attract different developers, and take fundamentally different architectural approaches.
This comparison breaks down both platforms honestly -- where each excels, where each falls short, and which one fits your specific needs.
Quick Verdict
Choose Aethir if: You need GPU compute for cloud gaming, want to participate as a hardware provider through their Cloud Host model, or are building at the intersection of gaming and Web3.
Choose io.net if: You are building AI/ML workloads and need mature developer tooling, transparent pricing, instant cluster deployment, and access to the largest decentralized GPU network. io.net offers Ray, Kubernetes, and container orchestration out of the box, with 25+ pre-deployed AI models via io.intelligence.
At a Glance
| Feature | io.net | Aethir |
|---|---|---|
| Network Scale | 320,000+ GPUs, 80,000+ CPUs | 435,000+ GPU containers |
| Geographic Reach | 130+ countries | 93 countries, 200+ locations |
| Architecture | DePIN with virtualization + orchestration | DePIN with bare metal containers |
| Primary Focus | AI/ML compute | AI compute + cloud gaming |
| Deployment Speed | Clusters in under 2 minutes | Variable (enterprise onboarding) |
| Pricing Transparency | Public, self-serve pricing | Enterprise/custom pricing |
| Developer Tooling | Ray, Kubernetes, Containers, VMs, Bare Metal | Aethir Developer SDK (launching Q2 2026) |
| AI Model Access | 25+ pre-deployed models (io.intelligence) | No managed model library |
| Token | $IO (Solana) | $ATH (Ethereum/multi-chain) |
| Validator System | Proof of Work + Proof of Time-Lock | Checker Nodes (91,000+) |
| Reported ARR | Not publicly disclosed | $147M+ (as of Q3 2025) |
Pricing Comparison
io.net Pricing
io.net publishes transparent, self-serve pricing with no minimum commitments and no enterprise gatekeeping:
| GPU | Hourly Rate | vs. AWS Equivalent |
|---|---|---|
| NVIDIA H100 SXM | $2.10 - $3.50/hr | ~70% cheaper |
| NVIDIA A100 80GB | $1.20 - $2.00/hr | ~70% cheaper |
| Mid-range inference GPUs | $0.40 - $1.50/hr | ~60-70% cheaper |
Key pricing characteristics: - Per-second billing -- pay only for active compute time - No contracts required -- start immediately, scale freely - No hidden infrastructure fees -- networking and storage included - Self-serve checkout -- no sales calls needed to get started
Aethir Pricing
Aethir's pricing model is less transparent to the public. Key characteristics:
- Token-denominated -- compute is purchased and settled in $ATH tokens
- Enterprise-oriented -- pricing is typically negotiated for larger deployments
- Cloud Host model -- hardware providers set their own pricing, similar to an Airbnb marketplace
- Claims of up to 86% savings vs. Google Cloud (per third-party reports, not independently verified)
Specific per-GPU hourly rates are not publicly listed on Aethir's website or documentation as of April 2026.
Pricing Verdict
io.net wins on pricing transparency. You can see exact costs before deploying. Aethir may offer competitive rates for enterprise contracts, but the lack of public, self-serve pricing makes it harder to evaluate without engaging their sales team. For developers and startups who want to estimate costs upfront, io.net's model is significantly more accessible.
Network Scale and Availability
io.net Network
io.net operates the largest decentralized compute network by verified GPU count:
- 320,000+ GPUs and 80,000+ CPUs aggregated from data centers, mining operations, and individual contributors across 130+ countries
- Hardware validation through Proof of Work (PoW) and Proof of Time-Lock (PoTL) ensures every GPU listed is real, active, and performing as advertised
- No waitlists -- if capacity exists on the network, you access it immediately
- Cluster deployment in under 2 minutes -- not hours, not days
The geographic distribution across 130+ countries means you can provision compute close to your users or data sources, reducing latency for inference workloads.
Aethir Network
Aethir reports an impressive container count, though measuring differently:
- 435,000+ GPU containers across 93 countries and 200+ locations
- 91,000+ Checker Nodes monitoring container quality and uptime
- Enterprise hardware including NVIDIA H100s (approximately 3,000 reported) and plans for H200 and B200 deployments
- Container-based architecture where each container represents a deployable compute unit
How to Read the Numbers
A direct comparison of "320,000+ GPUs" vs. "435,000+ containers" requires context. io.net counts individual GPU chips that have been hardware-validated. Aethir counts containers, which are software-defined compute units that may or may not map 1:1 to physical GPUs. Both numbers are large, but they measure different things.
What matters more than raw count is whether the GPU you need is available when you need it. io.net's self-serve model lets you verify availability instantly. Aethir's enterprise model requires engagement with their team for capacity planning.
Key Architectural Differences
Both io.net and Aethir are DePIN projects, but they take meaningfully different approaches to decentralized compute.
io.net: Virtualization + Orchestration Layer
io.net builds a full cloud computing stack on top of decentralized hardware:
- Virtualization layer abstracts heterogeneous GPUs into consistent, deployable clusters
- Orchestration through Ray and Kubernetes enables distributed training, batch inference, and complex ML pipelines
- Networking layer handles inter-node communication for multi-GPU workloads
- io.intelligence provides 25+ pre-deployed models with an OpenAI-compatible API -- you can run inference without managing infrastructure at all
- Agent Cloud supports persistent AI agents with always-on compute
- Confidential Computing enables privacy-preserving GPU workloads through hardware-level encryption
This architecture means developers interact with io.net similarly to how they would use AWS or GCP, but at DePIN economics.
Aethir: Bare Metal Containers + Three-Role System
Aethir uses a different model with three distinct network participants:
- Containers (compute providers) -- execute workloads on bare metal hardware, eliminating virtualization overhead
- Checkers (quality validators) -- monitor container performance and enforce SLAs
- Indexers (matchmakers) -- route user requests to appropriate containers based on requirements
The bare metal approach means less overhead per workload, but also less flexibility in how resources are combined and orchestrated. Aethir's architecture is optimized for single-container workloads rather than multi-node distributed training.
What This Means in Practice
If you need to spin up an 8-GPU Ray cluster for distributed training, io.net handles the orchestration natively. Aethir's architecture is better suited for single-container inference or rendering tasks where bare metal performance matters and multi-node coordination is less critical.
io.net's Confidential Computing capability is also a differentiator for regulated industries and privacy-sensitive AI workloads -- a feature Aethir does not currently offer.
Developer Experience and Tooling
io.net Developer Stack
io.net has invested heavily in developer experience:
- io.cloud -- deploy Ray clusters, Kubernetes clusters, containers, VMs, or bare metal with a self-serve dashboard
- io.intelligence -- 25+ pre-deployed models (Llama, Mistral, DeepSeek, and others) accessible via OpenAI-compatible API endpoints
- Agent Cloud -- persistent compute for autonomous AI agents
- Framework support -- PyTorch, TensorFlow, JAX, Hugging Face Transformers, vLLM
- Infrastructure options -- Ray, Kubernetes, Docker containers, VMs, bare metal
- CLI and API -- programmatic deployment and management
- Documentation -- comprehensive guides for common ML workflows
The developer experience is designed to be familiar. If you have used AWS SageMaker, Lambda Labs, or RunPod, the transition to io.net is straightforward. The OpenAI-compatible API for io.intelligence means you can switch inference providers by changing a single endpoint URL.
Aethir Developer Stack
Aethir's developer tooling is earlier in its lifecycle:
- Aethir Earth -- bare metal GPU access for AI workloads (training, fine-tuning, inference)
- Aethir Atmosphere -- low-latency GPU network optimized for cloud gaming
- GPU Dashboard -- real-time protocol monitoring
- Aethir Developer SDK -- announced for Q2 2026 launch, will include AI integration tools
- AI Workload Marketplace v2 -- GPU scheduling and dataset integration (roadmap item)
- Compute Reputation Layer -- Cloud Host reliability scoring (roadmap item)
Aethir's SDK and advanced developer tooling are largely roadmap items as of April 2026. The current experience is more enterprise-oriented, requiring direct engagement rather than self-serve deployment.
Developer Experience Verdict
io.net has a significant lead in developer tooling maturity. Self-serve deployment, multiple infrastructure abstractions (Ray, Kubernetes, containers, VMs, bare metal), and a managed model inference layer (io.intelligence) make it the more complete platform for AI/ML developers today. Aethir's planned SDK and marketplace improvements could narrow this gap, but they are not yet available.
Token Economics: $IO vs $ATH
Both projects use native tokens to power their network economies, but with different designs and ecosystems.
$IO Token
- Blockchain: Solana
- Role: Payment for compute, staking for supply-side providers, governance
- Ecosystem: Part of the Solana DePIN ecosystem alongside Helium, Render, and others
- Utility: Used to pay for GPU compute on io.cloud and io.intelligence; suppliers stake $IO to participate as compute providers
- Deflationary mechanics: Network revenue creates buy pressure through fee burns and staking rewards
$ATH Token
- Blockchain: Ethereum (with multi-chain expansion planned via EigenLayer ATH Vault)
- Role: Payment for compute, Cloud Host rewards, Checker Node rewards, staking
- Ecosystem: Ethereum-native with cross-chain ambitions; strategic compute reserve partnership with Nasdaq-listed Predictive Oncology
- Utility: All compute transactions settled in $ATH; Cloud Hosts earn $ATH for providing hardware; Checker Node operators earn daily $ATH rewards for quality verification
- Institutional backing: $344M ATH stake by Predictive Oncology positions $ATH as a "digital asset treasury" for institutional compute access
Token Comparison
| Aspect | $IO | $ATH |
|---|---|---|
| Chain | Solana | Ethereum (multi-chain planned) |
| Transaction speed | Sub-second finality | Ethereum L1 settlement |
| Gas costs | Minimal (Solana) | Higher (Ethereum), mitigated by L2s |
| DePIN ecosystem | Strong Solana DePIN cohort | Ethereum DePIN, smaller peer group |
| Institutional strategy | Organic network growth | Predictive Oncology partnership ($344M) |
| Staking | Supply-side provider staking | Cloud Host + Checker Node staking |
For developers, the token choice matters primarily for payment and settlement. io.net's Solana-based $IO benefits from lower transaction costs and faster settlement. Aethir's Ethereum-based $ATH carries higher gas costs but benefits from Ethereum's larger institutional ecosystem and planned EigenLayer integration.
When to Choose Aethir
Aethir is the better choice in these scenarios:
- Cloud gaming infrastructure. If you are building a cloud gaming platform, game streaming service, or real-time rendering pipeline, Aethir Atmosphere is purpose-built for low-latency GPU delivery to end users. io.net does not have a dedicated gaming compute product.
- Bare metal performance for single-node workloads. If your workload runs on a single GPU and you want zero virtualization overhead, Aethir's bare metal container approach eliminates the hypervisor layer entirely. This matters for latency-sensitive inference and real-time rendering.
- Ethereum-native Web3 integration. If your project lives on Ethereum or EVM chains and you want compute settlement on the same ecosystem, Aethir's $ATH token and planned EigenLayer integration keep everything within the Ethereum stack.
When to Choose io.net
io.net is the better choice in these scenarios:
- AI/ML development with mature tooling. If you need Ray clusters, Kubernetes orchestration, or managed model inference, io.net provides these out of the box. You can go from zero to a distributed training job in under 2 minutes without configuring infrastructure.
- Transparent, self-serve pricing. If you want to see exactly what you will pay before committing, io.net publishes GPU-specific hourly rates with per-second billing. No sales calls, no custom quotes, no token-denominated price ambiguity.
- Multi-GPU distributed training. If your workloads require coordination across multiple GPUs -- distributed training, large-scale batch inference, or complex ML pipelines -- io.net's virtualization and orchestration layer handles inter-node communication natively. This is not Aethir's architectural strength.
- Model inference without infrastructure management. io.intelligence provides 25+ pre-deployed models with an OpenAI-compatible API. You can run Llama, Mistral, DeepSeek, and other models by hitting an endpoint -- no GPU provisioning, no container management, no model deployment.
- Privacy-sensitive or regulated workloads. io.net's Confidential Computing capability enables hardware-level encryption for GPU workloads. If you are in healthcare, finance, or government and need privacy guarantees on decentralized infrastructure, io.net is currently the only DePIN platform offering this.
Frequently Asked Questions
Are io.net and Aethir competitors or partners?
Both. In 2024, Aethir and io.net announced a strategic collaboration to enhance decentralized computing capabilities. They share the broader goal of making GPU compute more accessible through DePIN. However, they compete for many of the same AI workload customers. Think of them as complementary in vision but competitive in practice -- similar to how AWS and Azure collaborate on open standards while competing fiercely for cloud market share.
Which has more GPUs: io.net or Aethir?
io.net reports 320,000+ verified GPUs. Aethir reports 435,000+ GPU containers. These numbers measure different things. io.net counts individual hardware-validated GPU chips. Aethir counts software-defined containers. A direct numerical comparison is misleading without understanding that a "container" and a "GPU" are not equivalent units. Both networks are large enough to serve substantial AI workloads.
Is io.net or Aethir cheaper?
io.net publishes specific rates: $2.10-$3.50/hr for H100 SXM, $1.20-$2.00/hr for A100 80GB. Aethir claims up to 86% savings vs. Google Cloud but does not publish standardized per-GPU rates. Without Aethir publishing comparable pricing, a direct cost comparison is not possible. io.net's transparency gives it an edge for cost-conscious developers who need to budget accurately.
Can I use either platform without holding crypto?
io.net supports fiat payment options for compute, making it accessible to developers who do not hold cryptocurrency. Aethir's compute transactions are settled in $ATH tokens, which requires acquiring the token. Check both platforms for current payment options, as these may evolve.
Which platform is better for AI agents?
io.net launched Agent Cloud specifically for persistent AI agent workloads, offering always-on compute optimized for autonomous agents. Aethir has outlined a 2026 vision for AI agents booking GPU inference through smart contracts, but this capability is on their roadmap rather than available today. For production AI agent deployments right now, io.net is the more ready platform.
Conclusion
io.net and Aethir represent two approaches to the same fundamental challenge: making GPU compute more accessible, affordable, and decentralized. Both are legitimate DePIN projects with large networks, active communities, and real traction.
The core difference is focus. Aethir splits its attention between AI compute and cloud gaming, offering bare metal containers and a marketplace model that works well for enterprise clients and gaming infrastructure.
io.net is purpose-built for AI/ML developers. Its virtualization layer, orchestration tools (Ray, Kubernetes), managed model inference (io.intelligence), Agent Cloud, and Confidential Computing create a more complete developer platform for machine learning workloads. Transparent pricing, self-serve deployment, and sub-2-minute cluster provisioning lower the barrier to entry significantly.
If you are building AI and need to start today, io.net gets you from zero to deployed faster with better tooling and clearer costs. If you are building cloud gaming infrastructure or want bare metal performance for single-container workloads, Aethir deserves serious consideration.
The best choice depends on what you are building. Both platforms are pushing the boundary of what decentralized infrastructure can deliver -- and that competition benefits everyone building in AI and Web3.
Ready to deploy? Start building on io.net – clusters deploy in under 2 minutes with no minimum commitment.